Typical industrial processes are extremely complex and receive substantially greater volumes of information than any human could possibly digest in its raw form. By way of example, it is not unheard of to have thousands of sensors and control elements (e.g., valve actuators) monitoring/controlling aspects of a multi-stage process within an industrial plant. These sensors are of varied type and report on varied characteristics of the process. Their outputs are similarly varied in the meaning of their measurements, in the amount of data sent for each measurement, and in the frequency of their measurements. As regards the latter, for accuracy and to enable quick response, some of these sensors/control elements take one or more measurements every second. Multiplying a single sensor/control element (e.g., tag) by thousands of sensors/control elements (a typical industrial control environment) results in an overwhelming volume of data flowing into the manufacturing information and process control system. Sophisticated data management and process visualization techniques have been developed to handle the large volumes of data generated by such system.
Highly advanced human-machine interface/process visualization systems exist today that are linked to data sources such as the above-described sensors and controllers. Such systems acquire and digest (e.g., filter) the process data described above. The digested process data in-turn drives a graphical display rendered by a human machine interface (HMI). Examples of such systems are the well-known Wonderware INTOUCH™ HMI software system for visualizing and controlling a wide variety of industrial processes and the ArchestrA™ (e.g., the application server or AppServer for INTOUCH™) comprehensive automation and information software open architecture designed to integrate and extend the life of legacy systems by leveraging the latest, open industry standards and software technologies.
Known HMIs render alert notifications based on averaged data values, which may unfortunately result in failure to alert users to certain conditions. Moreover, known HMIs and those that use conventional approaches (e.g., candlestick charts, bar charts) are unable to render graphical displays that include representations for a plurality of tags.